Altiscale is updating its Big Data-as-a-Service with an expanded Spark-as-a-Service offering that supports all major versions of Apache Spark. The new Altiscale Data Cloud 4.0 also features major upgrades to core Hadoop components, such as HDFS and YARN.
“Altiscale is dedicated to providing its customers with a full breadth of production-ready big data analytical options. That’s why we’ve been active in the Spark community from the very beginning,” said Raymie Stata, CEO and founder, Altiscale. “It’s also why Altiscale is ensuring that we support all major recent versions of Spark. Spark is evolving so rapidly that we want to ensure anything our customers rely on for Big Data analytics continues to be there for them.”
The latest version of the Altiscale Data Cloud also features the following updated capabilities:
- Apache Spark 1.5.0, which provides improved performance and stability. It offers enhanced support for Data Science APIs, especially with advances in DataFrames features and improved support for the R Language, making it a compelling release for data scientists.
- Apache Hadoop 2.7.1, so that customers can utilize YARN’s resource manager to deploy and manage long-running data access applications in Hadoop.
- Apache Hive 1.2.0, for access to enhanced SLQ Semantics and major performance improvements.
- Apache Pig 0.15.0, which now provides the capability to run Hive UDFs inside Pig as well as improved stability for Pig on Tez.
There are also improvements to the workflow manager, Apache Oozie (4.2.0) and to Apache Tez (0.7.0).
